@Article{MartinsTRAGGSPP:2018:ImDrMa,
author = "Martins, Minella Alves and Tomasella, Javier and Rodriguez, Daniel
Andres and Alval{\'a}, Regina C{\'e}lia S. and Giarolla,
Ang{\'e}lica and Garofolo, Lucas Lopes and Siqueira J{\'u}nior,
Jos{\'e} L{\'a}zaro and Paolicchi, Luiz Thiago Lucci Corr{\^e}a
and Pinto, Gustavo L. N.",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Centro
Nacional de Monitoramento e Alertas de Desastres Naturais
(CEMADEN)} and {Instituto Nacional de Pesquisas Espaciais (INPE)}
and {Centro Nacional de Monitoramento e Alertas de Desastres
Naturais (CEMADEN)} and {Instituto Nacional de Pesquisas Espaciais
(INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and
{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)}",
title = "Improving drought management in the Brazilian semiarid through
crop forecasting",
journal = "Agricultural Systems",
year = "2018",
volume = "160",
pages = "21--30",
month = "Feb.",
note = "{Pr{\^e}mio CAPES Elsevier 2023 - ODS 2: Fome zero e Agricultura
sustent{\'a}vel} and {Pr{\^e}mio CAPES Elsevier 2023 - ODS 8:
Trabalho decente e crescimento econ{\^o}mico}",
keywords = "Maize, Crop forecast, AquaCrop, Eta RCM.",
abstract = "In this paper, we evaluated the performance of the model AquaCrop
for crop yield forecasting in the Brazilian semiarid (BSA) using
meteorological observation and Eta model seasonal climate
forecasts as input data. The study area is characterized by low
rainfall that is poorly distributed throughout the rainy season;
thus, the region's agricultural productivity is vulnerable to
climate conditions. AquaCrop was first calibrated using field
experiments and subsequently applied to simulate an operational
crop yield forecast system for maize under rainfed conditions.
Simulations were performed with daily data for 37 growing seasons
for the period 20012010. The seasonal climate forecast was used in
combination with observed meteorological data to anticipate the
crop forecast. Soil characteristics were derived from pedotransfer
functions (PTFs). We were able to demonstrate the ability of the
seasonal crop yield forecast system to provide timely and accurate
information about maize yield at least 30 days in advance of the
harvest. The development of improved crop yield forecasting system
is crucial for implementing drought-preparedness measures in the
BSA region.",
doi = "10.1016/j.agsy.2017.11.002",
url = "http://dx.doi.org/10.1016/j.agsy.2017.11.002",
issn = "0308-521X",
language = "en",
targetfile = "martins_improving.pdf",
urlaccessdate = "02 maio 2024"
}